Fig. 1: The SDG space in 2022.
Panel a, Network representation of the SDG space. The node color represents goal sustainability index (GSI), the edge color and shape represent the similarity between two indicators regarding revealed comparative advantage (RCA), and the node size is the node degree, representing the number of edges connected to the node. Panel b, The heat map of similarity (> = 0.7) between SDG indicators regarding RCA. Panel c, The country sustainability index (CSI) of nations. The map color represents CSI. In Panel a, the proximity between SDG indicators in the nation-indicator bipartite network is defined by the conditional probability that two indicators are co-specialized within a nation. RCA is used to assess which country specializes or has relative advantage in which area. If a country c has a higher share of SDG indicator i than the world average, then RCAc,i > 0, which means that this country is considered to have relative advantage in SDG indicator i. GSI and CSI are twin clustering indicators, which are calculated based on RCA of indicators using the method developed by Hidalgo and Hausmann23 (see Methods). The algorithm is equivalent to finding the eigenvalues of a matrix and is related to a spectral clustering algorithm that divides SDG indicators (or countries) into two groups: those with higher and lower GSI values (or countries with higher and lower CSI values). As a result of this reflections algorithm, countries with high CSI values tend to dominate the high-GSI indicators, and vice versa. Most high-CSI countries (blue background countries in c) have high SDG scores, and most low-CSI countries have low SDG scores (Supplementary Table 1).
